Triple

T1521262
Position Surface form Disambiguated ID Type / Status
Subject Pilger E32232 entity
Predicate hasNotableBearer P458 FINISHED
Object Peter Pilger
Peter Pilger is an individual notable enough to be recognized as a bearer of the surname Pilger.
 E175553 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Peter Pilger | Statement: [Pilger, hasNotableBearer, Peter Pilger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Peter Pilger
Context triple: [Pilger, hasNotableBearer, Peter Pilger]
  • A. Peter Sargeant
    Peter Sargeant was a colonial-era jurist who served as a judge on the Court of Oyer and Terminer.
  • B. Steven Pemberton
    Steven Pemberton is a British computer scientist and software engineer known for his work on programming languages, web standards, and contributions to the development of ABC and early Python influences.
  • C. John Hull
    John Hull was a prominent 17th-century Boston merchant, silversmith, and colonial official best known for serving as the Massachusetts Bay Colony’s mintmaster.
  • D. Sam Pilger
    Sam Pilger is a British sports journalist and writer known for his coverage of football and contributions to major publications.
  • E. Peter Godfrey
    Peter Godfrey was a British-born actor and director known for his work in mid-20th-century film and television, particularly in Hollywood.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Peter Pilger
Triple: [Pilger, hasNotableBearer, Peter Pilger]
Generated description
Peter Pilger is an individual notable enough to be recognized as a bearer of the surname Pilger.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Peter Pilger
Target entity description: Peter Pilger is an individual notable enough to be recognized as a bearer of the surname Pilger.
  • A. Peter Sargeant
    Peter Sargeant was a colonial-era jurist who served as a judge on the Court of Oyer and Terminer.
  • B. Steven Pemberton
    Steven Pemberton is a British computer scientist and software engineer known for his work on programming languages, web standards, and contributions to the development of ABC and early Python influences.
  • C. John Hull
    John Hull was a prominent 17th-century Boston merchant, silversmith, and colonial official best known for serving as the Massachusetts Bay Colony’s mintmaster.
  • D. Sam Pilger
    Sam Pilger is a British sports journalist and writer known for his coverage of football and contributions to major publications.
  • E. Peter Godfrey
    Peter Godfrey was a British-born actor and director known for his work in mid-20th-century film and television, particularly in Hollywood.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a885e9b0ac819093a9806ad0efc82c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a907f071848190a5fb8fa1b97ef4de completed March 5, 2026, 4:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad308f99d8819095c2ed404d4170b3 completed March 8, 2026, 8:17 a.m.
NEDg Description generation batch_69ad3122d16081909cc0ad2fc55ee761 completed March 8, 2026, 8:19 a.m.
NED2 Entity disambiguation (via description) batch_69ad31c7a2b08190a75ee4face596565 completed March 8, 2026, 8:22 a.m.
Created at: March 4, 2026, 7:26 p.m.